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The 7th International Conference on NLP & Information Retrieval (NLPI 2026) invites high quality research contributions from academia, industry, and government. NLPI has established itself as a global forum for presenting cutting edge advances in natural language processing, information retrieval, and the rapidly evolving landscape of AI driven language technologies.

NLPI 2026;     Email: nlpi@csitec2026.org

ore NLP Tasks & Linguistic Foundations Tokenization, POS tagging, chunking, and shallow parsing Parsing, grammatical formalisms, and syntactic analysis Lexical semantics and semantic role labeling Discourse, pragmatics, and dialogue structure Phonology, morphology, and linguistic theory Linguistic resources, corpora, and annotation methodologies Large Language Models & Advanced NLP Foundation models and large language models (LLMs) Prompt engineering, fine tuning, and instruction following Hallucination detection and mitigation Multilingual, cross lingual, and low resource NLP Efficient NLP: compression, distillation, and acceleration

Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH

Speech Translation; Human Interpretation; Multilingual AI Assistant; Speech Processing; Human-Computer Interaction

Human-Computer Interaction, User Experience, Virtual Reality,    Linguistics

European Society for the Study of English

The rapid development of AI and its integration into translator training and translation practices have led to numerous changes in both academia (Bada & Schumacher, 2024; Loock, 2025) and the translation industry (Girletti & Lefer, 2024), hence a need for trainees and professionals to adapt to an ever-changing field. The necessity of mastering new AI skills, namely prompt engineering (He, 2024: 316), leads both lecturers and professionals to reinvent themselves more than ever. Although the recent AI developments have led to the use of MT for many text types that were considered, until recently, to be AI-resistant, human intervention is still needed to maintain professional quality standards, particularly for literary translation (Hansen & Esperança-Rodier, 2022: 185), creative domains (dubbing, subtitling, localisation) (e.g. Jiménez-Crespo, 2024: 18) and specialised translation (terminology management, polysemy) (Kübler et al., 2024).